Abstract
Using computer technology to recognize emotion is the key to realize high-level human-computer interaction. Compared with facial and behavioral, physiological data such as EEG can detect real emotions more efficiently to improving the level of human-computer interaction. Because of the traditional EEG equipment is complex and not portable enough, the single channel EEG device is cheap and easy to use that has attracted our attention. In this paper, the main goal of this study is to use a single channel EEG device to acquire the EEG signal, which has been decomposed to corresponding frequency bands and features have been extracted by the Discrete Wavelet Transforms (DWT). Then, classify three different emotional states data so as on to achieve the purpose of emotion recognition. Our experimental results show that three different emotional states include positive, negative and neutral can be classified with best classification rate of 92%. Moreover, using the high-frequency bands, specifically gamma band, has higher accuracy compared to using low-frequency bands of EEG signal.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China (No. 61701104), and by the Science and Technology Development Plan of Jilin Province, China (No.20190201194JC, and No. 20200403039SF).
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Zhou, T.H., Liang, W.L., Liu, H.Y., Pu, W.J., Wang, L. (2020). Wavelet-Based Emotion Recognition Using Single Channel EEG Device. In: Huang, DS., Premaratne, P. (eds) Intelligent Computing Methodologies. ICIC 2020. Lecture Notes in Computer Science(), vol 12465. Springer, Cham. https://doi.org/10.1007/978-3-030-60796-8_44
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DOI: https://doi.org/10.1007/978-3-030-60796-8_44
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